The combination of computer science, medical imaging technology and biology has turned cancer research upside down. This collaborative project, which integrates expertise from many fields and uses advanced methods such as deep learning for accurate pixel-wise segmentation of cell images to allow other researchers working in cancer research to carry out precise identification at the level of individual cells. These subtle algorithms reveal how cancer cells behave, what form they take and the ways in which they interact--in particular giving us a lot of information on cancer at its most microscopic. Thanks to cutting-edge segmentation, researchers can determine how to treat cancer cells depending on their specific characteristics separately. This not only improves diagnostic accuracy and treatment efficacy but also better suits monitoring patients diagnosed with this disease. The synergy is multidisciplinary; the accumulation of scientific understanding will also help transform cancer diagnosis, treatment strategies and therapeutic monitoring to effect better patient outcomes